Wang Huifen, Zhu Weiwei, Lei Jun, Liu Zhibo, Cai Yudie, Wang Shuaifeng, Li Ang
Gene Hospital of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Infectious Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Cell Infect Microbiol. 2025 Mar 24;15:1573216. doi: 10.3389/fcimb.2025.1573216. eCollection 2025.
Given the heightened focus on high-risk populations, this study aimed to provide insights into early susceptibility and preventive strategies for colorectal cancer (CRC) by focusing on high-risk populations. In this research, fecal samples from 1,647 individuals across three discovery cohorts and nine external validation cohorts were sequenced using whole-genome metagenomic sequencing. A prediction model based on random forest was constructed using the nine external cohorts and independently validated with the three discovery cohorts. A disease probability (POD) model based on microbial biomarkers was developed to assess CRC risk. We found that the gut microbiome composition of CRC relatives differed from that of controls, with enrichment of species such as and and a reduction in beneficial genera like and . Additionally, dietary red meat intake emerged as a risk factor. The POD model indicated an elevated risk of CRC in unaffected relatives. The findings suggest that the POD for CRC may be increased in unaffected relatives or individuals living in shared environments, although this difference did not reach statistical significance. Our study introduces a novel framework for assessing the risk of colorectal cancer in ostensibly healthy individuals.
鉴于对高危人群的关注度不断提高,本研究旨在通过关注高危人群,深入了解结直肠癌(CRC)的早期易感性和预防策略。在本研究中,对来自三个发现队列和九个外部验证队列的1647名个体的粪便样本进行了全基因组宏基因组测序。使用九个外部队列构建了基于随机森林的预测模型,并在三个发现队列中进行了独立验证。开发了一种基于微生物生物标志物的疾病概率(POD)模型来评估CRC风险。我们发现,CRC亲属的肠道微生物群组成与对照组不同,某些物种如 和 富集,而有益菌属如 和 减少。此外,膳食红肉摄入量是一个风险因素。POD模型表明未受影响亲属患CRC的风险升高。研究结果表明,未受影响的亲属或生活在共同环境中的个体患CRC的POD可能会增加,尽管这种差异未达到统计学意义。我们的研究引入了一个评估表面健康个体患结直肠癌风险的新框架。